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This paper addresses bird song analysis based on semi-automatic annotation. Research in animal behavior, especially with birds, would be aided by automated (or semiautomated) systems that can localize sounds, measure their timing, and identify their source. This is difficult to achieve in real environments where several birds may be singing from different locations and at the same time. Analysis of...
Birds are frequently vocal. Monitoring their songs and calls has provided much useful information about their ecology and behavior. Recording bird songs and locations can be resource intensive, frequently requiring two or more observers, causing considerable disturbance and possible only for short times. Passive arrays of acoustic sensors offer the possibility of greatly increasing our ability to...
In this paper, we present a birdsong-phrase segmentation and verification algorithm that is robust to limited training data, class variability, and noise. The algorithm comprises a noise-robust, Dynamic-Time-Warping (DTW)-based segmentation and a discriminative classifier for outlier rejection. The algorithm utilizes DTW and prominent (high energy) time-frequency regions of training spectrograms to...
A bird phrase segmentation method using entropy-based change point detection is proposed. Spectrograms of bird calls are usually sparse while the background noise is relatively white. Therefore, considering the entropy of a sliding time-frequency block on the spectrogram, the entropy dips when detecting a signal and rises when the signal ends. Rather than applying a hard threshold on the entropy to...
Acoustic sensor arrays are recognized as an important development for field studies of animal behavior and ecology. While birds live in a 3D world and all dimensions seem important for most birds, use of these arrays has been limited almost entirely to 2D. A notable exception was the development by S. Asgari of Approximate Maximum Likelihood methods for 3D, tested with recorded sounds. Here we describe...
In this paper, we present simulation and experimental studies of localization and source separation for a bio-complexity bird study based on a new wireless acoustic array node named Voxnet. The Approximate Maximum Likelihood (AML) method is used to estimate blindly the direction-of-arrivals (DOAs) of sources which can be used to both locate the sources using a DOA-based localization method and generate...
In this paper, we present simulation and experimental studies of multiple bird source separation based on the Voxnet acoustic array node. The Approximate Maximum Likelihood (AML) method is used to estimate blindly the direction-of-arrivals (DOAs) of the sources to generate the steering vectors in order to separate the sources via beamforming. Simulation and measured data confirmed the proper operations...
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